Robust \(H_{\infty}\) filtering for uncertain impulsive stochastic systems under sampled measurements
type: Item
instance of: scholarly article
title: Robust \(H_{\infty}\) filtering for uncertain impulsive stochastic systems under sampled measurements
zbMATH Open document ID: 1012.93063
DOI: 10.1016/S0005-1098(02)00248-0
author: Shengyuan Xu
author: Tongwen Chen
published in: Automatica
publication date: 2003-04-27T00:00:00Z
review text: This paper is concerned with the problem of robust \(H_{\infty}\) filtering for uncertain impulsive stochastic systems under sampled measurements. The parameter uncertainties are assumed to be time-varying norm-bounded. The aim is to design a stochastically stable filter, using the locally sampled measurements, which ensures both the robust stochastic stability and a prescribed level of \(H_{\infty}\) performance for the filtering error dynamics for all admissible uncertainties. A sufficient condition for the existence of such a filter is proposed in terms of certain linear matrix inequalities (LMIs). When these LMIs are feasible, an explicit expression of a desired filter is given. An example is provided to demonstrate the effectiveness of the proposed approach.
reviewed by: Sotiris K. Ntouyas
Mathematics Subject Classification ID: 93E11
Mathematics Subject Classification ID: 93B36
Mathematics Subject Classification ID: 93C57
Mathematics Subject Classification ID: 93E15
Mathematics Subject Classification ID: 93D09
Mathematics Subject Classification ID: 34A37
zbMATH DE Number: 1900991
zbMATH Keywords: \(H_{\infty}\) filtering
zbMATH Keywords: impulsive systems
zbMATH Keywords: linear matrix inequality
zbMATH Keywords: robust filtering
zbMATH Keywords: sampled measurements
zbMATH Keywords: stable filter
zbMATH Keywords: robust stochastic stability
MaRDI profile type: Publication
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description: scientific article; zbMATH DE number 1900991